Every year the amount of data electronically stored and then accessed by users grows substantially. One example of this has been driven by the increased viability of high-density optical storage discs. There are now many organisations which send out data in the form of optical discs at regular intervals. The data can either be data which has only recently become available to the general public, such as newly published or granted patent specifications, or already existing publications which have been collated. It will be appreciated that whilst modern technology allows a user to scan rapidly through the contents of an optical disc, problems arise when it is required to scan through the contents of a large number of such discs. An acute example as to how such a problem can arise is when users have optical disc databases of patent information which is updated on a monthly basis in response to the publication of pending or granted patent specifications. Whilst it may well be advantageous for a user to scan through one or more discs for relevant information, any attempt to extract data over a greater period of time becomes labour intensive. A solution to this problem is to down-load the text stored in a recently received optical disc and combine this text with the previously received text in a single large database. It will be appreciated than when a single optical disc can hold the contents of 10,000 substantial documents such as patent specifications a single database holding all this information must have a very substantial capacity. It has accordingly become quite common to store data, and in particular textual information, in compressed form. Normally text is stored on the optical disc in the widely accessible ASCII format. Text compression algorithms are known and can reduce the storage requirements for large quantities of text originally stored in ASCII format by as much as 70%. Some compression algorithms are known as "lossy" as they cause the problem that the actual format and layout of the text is lost on decompression. Other algorithms maintain the format of the text. However both types of known compression algorithm have the drawback that it is very difficult to index nested sections within the complete text and decompress these sections alone. It can thus be seen that any user of a database has to meet two requirements which at present conflict. Either the data can be stored in uncompressed form so that it can be readily indexed but will take up a substantial amount of expensive storage capacity, or the data can be compressed so as to reduce the required storage capacity but with the attendant problem that the data is then difficult to access and extract.